| Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge EE Bron, M Smits, WM Van Der Flier, H Vrenken, F Barkhof, P Scheltens, ... NeuroImage 111, 562-579, 2015 | 287 | 2015 |
| Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation J Wen, E Thibeau-Sutre, M Diaz-Melo, J Samper-González, A Routier, ... Medical image analysis 63, 101694, 2020 | 237 | 2020 |
| Morphometry of anatomical shape complexes with dense deformations and sparse parameters S Durrleman, M Prastawa, N Charon, JR Korenberg, S Joshi, G Gerig, ... NeuroImage 101, 35-49, 2014 | 228 | 2014 |
| Statistical models of sets of curves and surfaces based on currents S Durrleman, X Pennec, A Trouvé, N Ayache Medical image analysis 13 (5), 793-808, 2009 | 193 | 2009 |
| Toward a comprehensive framework for the spatiotemporal statistical analysis of longitudinal shape data S Durrleman, X Pennec, A Trouvé, J Braga, G Gerig, N Ayache International journal of computer vision 103 (1), 22-59, 2013 | 155 | 2013 |
| Cognitive and neuroimaging features and brain β-amyloidosis in individuals at risk of Alzheimer's disease (INSIGHT-preAD): a longitudinal observational study B Dubois, S Epelbaum, F Nyasse, H Bakardjian, G Gagliardi, ... The Lancet Neurology 17 (4), 335-346, 2018 | 149 | 2018 |
| Spatiotemporal atlas estimation for developmental delay detection in longitudinal datasets S Durrleman, X Pennec, A Trouvé, G Gerig, N Ayache International Conference on Medical Image Computing and Computer-Assisted …, 2009 | 125 | 2009 |
| Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data J Samper-González, N Burgos, S Bottani, S Fontanella, P Lu, A Marcoux, ... NeuroImage 183, 504-521, 2018 | 116 | 2018 |
| Inferring brain variability from diffeomorphic deformations of currents: an integrative approach S Durrleman, X Pennec, A Trouvé, P Thompson, N Ayache Medical image analysis 12 (5), 626-637, 2008 | 112 | 2008 |
| Statistical models of currents for measuring the variability of anatomical curves, surfaces and their evolution S Durrleman Université Nice Sophia Antipolis, 2010 | 108 | 2010 |
| A precision medicine initiative for Alzheimer’s disease: the road ahead to biomarker-guided integrative disease modeling H Hampel, SE O’Bryant, S Durrleman, E Younesi, K Rojkova, ... Climacteric 20 (2), 107-118, 2017 | 103 | 2017 |
| Comparison of the endocranial ontogenies between chimpanzees and bonobos via temporal regression and spatiotemporal registration S Durrleman, X Pennec, A Trouvé, N Ayache, J Braga Journal of Human Evolution 62 (1), 74-88, 2012 | 102 | 2012 |
| Registration, atlas estimation and variability analysis of white matter fiber bundles modeled as currents S Durrleman, P Fillard, X Pennec, A Trouvé, N Ayache NeuroImage 55 (3), 1073-1090, 2011 | 98 | 2011 |
| Revolution of Alzheimer precision neurology. Passageway of systems biology and neurophysiology H Hampel, N Toschi, C Babiloni, F Baldacci, KL Black, ALW Bokde, ... Journal of Alzheimer's Disease 64 (s1), S47-S105, 2018 | 97 | 2018 |
| A statistical model for quantification and prediction of cardiac remodelling: Application to tetralogy of fallot T Mansi, I Voigt, B Leonardi, X Pennec, S Durrleman, M Sermesant, ... IEEE transactions on medical imaging 30 (9), 1605-1616, 2011 | 95 | 2011 |
| Early cognitive, structural, and microstructural changes in presymptomatic C9orf72 carriers younger than 40 years A Bertrand, J Wen, D Rinaldi, M Houot, S Sayah, A Camuzat, C Fournier, ... JAMA neurology 75 (2), 236-245, 2018 | 82 | 2018 |
| Learning spatiotemporal trajectories from manifold-valued longitudinal data JB Schiratti, S Allassonniere, O Colliot, S Durrleman Advances in neural information processing systems 28, 2015 | 79 | 2015 |
| Sparse adaptive parameterization of variability in image ensembles S Durrleman, S Allassonnière, S Joshi International Journal of Computer Vision 101 (1), 161-183, 2013 | 69 | 2013 |
| Deformetrica 4: an open-source software for statistical shape analysis A Bône, M Louis, B Martin, S Durrleman International Workshop on Shape in Medical Imaging, 3-13, 2018 | 62 | 2018 |
| A Bayesian mixed-effects model to learn trajectories of changes from repeated manifold-valued observations JB Schiratti, S Allassonnière, O Colliot, S Durrleman The Journal of Machine Learning Research 18 (1), 4840-4872, 2017 | 53 | 2017 |
Olivier ColliotResearch Director at CNRS, ARAMIS LabПотвърден имейл адрес: upmc.fr
